Non-linear association of atherogenic index of plasma with insulin resistance and type 2 diabetes: a cross-sectional study
Jinan University · Southern University of Science and Technology · +4 more institutions
Abstract
Although there is numerous evidence on the epidemiological risk factors for insulin resistance (IR)-related metabolic diseases, there is still insufficient evidence to explore the non-linear association of Atherogenic Index of Plasma (AIP) with IR. Therefore, we aimed to elucidate the non-linear relationship between AIP and IR and type 2 diabetes (T2D).
This cross-sectional study was conducted in the National Health and Nutrition Survey (NHANES) from 2009 to 2018. A total of 9,245 participants were included in the study. The AIP was calculated as log10 (triglycerides/high-density lipoprotein cholesterol). The outcome variables included IR and T2D defined by the 2013 American Diabetes Association guidelines. The weighted multivariate linear regression, weighted multivariate logistic regression, subgroup analysis, generalized additive model, smooth fitting curve and two-part logistic regression were adopted to reveal the relationship of AIP with IR and T2D.
Citation impact
- FWCI
- 42.91
- Percentile
- 100%
- References
- 49
Authors
6- BYBei YinCorresponding
Jinan University, Southern University of Science and Technology, Southern Medical University Shenzhen Hospital, Shenzhen Second People's Hospital
- ZWZihong Wu
Chengdu University of Traditional Chinese Medicine
- YXYaqing Xia
Guangzhou University of Chinese Medicine
- SXShunqiang Xiao
Jinan University, Southern University of Science and Technology, Southern Medical University Shenzhen Hospital, Shenzhen Second People's Hospital
- LCLing‐Ling Chen
Jinan University, Southern University of Science and Technology, Southern Medical University Shenzhen Hospital, Shenzhen Second People's Hospital
Topics & keywords
- Medicine
- Body mass index
- Insulin resistance
- Internal medicine
- Type 2 diabetes
- Cross-sectional study
- Diabetes mellitus
- Logistic regression
- Good health and well-being